#1 most frequent
United States of America
51.7%4,795 installations of 9,271
What is GitHub Copilot?
GitHub Copilot is an AI-powered developer tool that, according to the vendor, aims to assist developers in writing code more efficiently by reducing boilerplate code and improving productivity. It is designed for both individual developers and businesses of all sizes. The tool is commonly used by professionals in various industries, including software developers, web developers, mobile app developers, data scientists, and DevOps engineers.
Categories & Use Cases
Who Buys & Uses GitHub Copilot
#2 most frequent
Canada
5.7%530 installations of 9,271
#3 most frequent
India
5.6%517 installations of 9,271
CoPilot works with any IDE including VS code and PHP Storm.
Use Cases and Deployment Scope
GitHub Copilot is used in my company to help developers write better and structured code. We develop applications using PHP Laravel, but sometimes developers don't follow standard coding practices, which can lead to issues. They also need help understanding how to define write logics via coding terms. GitHub Copilot has been incredibly helpful to my team, enabling them to write better code and work faster.
Pros
- Make code development faster and quicker.
- Helps write better code standards for projects.
- Provide the latest functions from the technology.
- Notifies about the deprecated functions.
Cons
- Copilot provides a great level of code suggestions. It works great for backend code, but can be improved for front-end code, including styling.
Return on Investment
- CoPilot has saved my development time.
- CoPilot has provided good-quality code to keep the client happy.
Usability
Alternatives Considered
Cursor
Other Software Used
Cursor, Anthropic Claude, Google Gemini, Azure OpenAI Service, Bolt, National Instruments Vision Builder AI
Best AI Tool For real Time Code Generation
Use Cases and Deployment Scope
We use GitHub Copilot in our organization primarily for software development especially for code generation and code suggestion, its saves lots of time and helps us to develop our app faster with efficient code. Nowadays it become more powerful with the agent mode, now it has a capacity to perform very complex task with high success rate, if efficient prompt is provided.
Pros
- Real time code suggestions are really fast and accurate I liked it.
- After introduction of Agent Mode now it can handle very complex task with high accuracy.
- Get better performance, if use it with MCP server.
Cons
- The only issue I faced is the context token size, it can be increase.
- Sometime with agent mode it takes too much time, which can be reduced but I understand it also depends on the complexity of the given task.
Return on Investment
- It has very positive impact in our organization, it saves lots of time.
- Helps us to build more efficient and secure Apps.
- Helps in fast product development.
Usability
Alternatives Considered
Anthropic Claude
Other Software Used
Anthropic Claude
Beyond the Hype A Developers Perspective on GitHub Copilot.
Use Cases and Deployment Scope
We use github copilot as a coding assistant mainly. We have been using the IDE integrations of Github Copilot in both IntelliJ IDEA as well as VSCode. It has acted as a very strong coding assistant, providing valuable suggestions and feedback to the code. It also suggests code for problems that I describe, thus helping me "vibe-code" in my work. We have not yet procured the agentic capabilities for github copilot so my review is based on the non-agentic version.
Pros
- Reading codebases and understanding the same.
- Providing valuable code snippets for problems or tasks that I describe in English.
- Also helps with other supplementary technical activities, such as, from time to time, I have asked it to suggest places where I can add logs and suggest how I can monitor those logs on Splunk via a dashboard. It has helped me with both.
Cons
- Sometimes code generated by Copilot is not of the best quality, doesn't handle all the edge cases, and misses some requirements.
- I have noticed that the Copilot is not the best at analyzing large monolithic codebases and placing them in their context. It has suggested to me APIs and methods from time to time that don't exist in my codebases.
- I would have loved it if there were a deeper integration available with the IDEs. Although the IntelliJ IDEA extension is decent, I would have loved it if there were, say, a direct integration available of the GitHub Copilot agent with the IntelliJ Debugger.
Return on Investment
- Has improved our dev velocity for simple tasks such as dependency updates or addressing SSRF vulnerabilities in our code bases by at least 50%.
- Our Engineers use Copilot to even generate dashboards on Splunk. Thereby, not just helping with coding but also with observability and monitoring.
- A slightly negative ROI may be that new grads into our company often blindly rely on GitHub Copilot-generated code and are not then able to demonstrate analytical and critical thinking ability. They struggle when it comes to verifying if the AI-generated code is accurate or not.
Usability
Alternatives Considered
Augment, Google Gemini, Uniqodo, Windsurf and Cursor
Other Software Used
Microsoft Visual Studio Code, GitHub, Atlassian Jira, Postman
Use it, you'll thank me for telling you.
Use Cases and Deployment Scope
I use GitHub Copilot daily. It became a great time saver from the first day I started using it, and it has only gotten better since.
It helps me write the boring boilerplate code, giving great suggestions for what to write next, and it gives me ideas on where to go from my current location and onwards.
It helps me write the boring boilerplate code, giving great suggestions for what to write next, and it gives me ideas on where to go from my current location and onwards.
Pros
- Code completion
- Adding fields to forms
- Suggestions on implementations
- Writing the basic tests
Cons
- It takes a while to trigger, and if you've already moved on when it does, your suggestion just flashes on the screen and then disappears again.
- Multilingual data
- It often keeps repeating itself even though you've deviated from its suggestion.
- The "question-answer" functionality sometimes overwrites existing code with // code... comments.
Return on Investment
- Our ROI of the purchase of Copilot was met in less than a day. The timesave cannot be overstated
- Programmer boredom/dissatisfaction is down because of less repetetive crud work.
Usability
Other Software Used
Microsoft Visual Studio, Azure App Service, Progress Telerik
GitHub Copilot AI Assistant Inside the IDE.
Use Cases and Deployment Scope
Development teams in our organization use GitHub Copilot to improve productivity while working on .NET applications in the Visual Studio IDE. Before using GitHub Copilot, our developers depended on Google searches, AI tools, and developer forums to get help with development tasks. With GitHub Copilot now integrated into Visual Studio, they have a one-stop solution that eases their development process.
Pros
- Code Completions.
- Fixing Bugs in Code.
- Optimizing Code.
Cons
- Chat responses can be improved.
- Accuracy needs improvement.
- Ease of Use can be made better.
Return on Investment
- Faster Development Time.
- Learning Curve is Reduced.
- Lowered Development Costs.
Usability
Alternatives Considered
ChatGPT, Perplexity and xAI Grok
Other Software Used
xAI Grok, Perplexity, ChatGPT, Microsoft Teams